Submitted by Jos? Henrique Henrique (jose.neves@ufvjm.edu.br) on 2017-06-06T21:08:54Z No. of bitstreams: 2 jose_lucas_camargos.pdf: 1772896 bytes, checksum: ed61126d3964190579d1888b21edf3aa (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Rodrigo Martins Cruz (rodrigo.cruz@ufvjm.edu.br) on 2017-06-22T15:30:03Z (GMT) No. of bitstreams: 2 jose_lucas_camargos.pdf: 1772896 bytes, checksum: ed61126d3964190579d1888b21edf3aa (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2017-06-22T15:30:03Z (GMT). No. of bitstreams: 2 jose_lucas_camargos.pdf: 1772896 bytes, checksum: ed61126d3964190579d1888b21edf3aa (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2017 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior (CAPES) / Funda??o de Amparo ? Pesquisa do Estado de Minas Gerais (FAPEMIG) / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico (CNPq) / O objetivo deste trabalho foi avaliar a influ?ncia da redu??o de parcelas em algumas medi??es de invent?rio florestal cont?nuo na modelagem do crescimento e produ??o de um povoamento de Eucalyptus sp. O modelo de Clutter foi utilizado na modelagem do crescimento e da produ??o florestal, a partir de dados selecionados de 374 parcelas distribu?das em 172 talh?es. Foram utilizadas tr?s alternativas de modelagem: sem estratifica??o do povoamento, com estratifica??o do povoamento e um conjunto de 30 simula??es. Estas simula??es foram amostras de 40 parcelas aleat?rias cada, sem estratifica??o, com o objetivo de possibilitar uma an?lise geral dos efeitos do fen?meno estudado. Em todas as alternativas, foi realizada a modelagem do crescimento e da produ??o sem considerar redu??es nas medi??es de invent?rio florestal cont?nuo e considerando tr?s situa??es de redu??o. As situa??es consideradas foram medi??es de 25%, 50% e 75% das parcelas do invent?rio florestal cont?nuo nas medi??es dois e quatro, e 100% nas medi??es um, tr?s e cinco. Esta mesma metodologia foi repetida, por?m com a utiliza??o do modelo de regress?o n?o linear Log?stico, acrescido de um fator de corre??o. Ambos os modelos apresentaram boa precis?o para a predi??o e proje??o do volume do povoamento em idades futuras. O modelo Log?stico com fator de corre??o, entretanto, foi mais preciso que o modelo de Clutter. Para ambos os modelos foi constatado que n?o houveram perdas significativas de precis?o acarretadas pelas redu??es no n?mero de parcelas em algumas medi??es do invent?rio florestal cont?nuo. Para a modelagem do crescimento e da produ??o, ? recomendado que estas redu??es sejam criteriosas e que preferencialmente a ?ltima medi??o n?o seja reduzida. / Disserta??o (Mestrado) ? Programa de P?s-Gradua??o em Ci?ncia Florestal, Universidade Federal dos Vales do Jequitinhonha e Mucuri, 2017. / This study had as object to evaluate the influence of the reduction of plots at some measurements of continuous forest inventory in the growth and yield modeling of a Eucalyptus sp. forest stand. The Clutter model was used in forest growth and yield modeling, using selected data of 374 distributed plots in 172 forest compartments. It were used three modeling alternatives: without stratification of the forest stand, with stratification of the forest stand and a set of 30 simulations. These simulations were samples of 40 plots each one, without stratification, objectifying a general analysis about the studied phenomenon. To all the alternatives, it was made the forest growth and yield modeling without considering reductions in continuous forest inventory measurements and considering three reduction situations. The considered situations were measurements of 25%, 50% and 75% of the continuous forest inventory plots in the measures two and four, and 100% in the measures one, three and five. This same methodology was repeated, but using the Logistic nonlinear regression model, plus a correction factor. Both models had good precision to predicting and projecting the forest stand volume at future ages. The Logistic model with a correcting factor, however, had best precision than the Clutter model. For both models it was found that there was not significant losses of accuracy caused by reductions in the number of plots at some continuous forest inventory measurements. To forest growth and yield modeling, it is recommended for these reductions to be judicious and preferably the last measurement to not be reduced.

Submitted by (ana.araujo@ufrpe.br) on 2016-07-05T18:07:15Z No. of bitstreams: 1 Fabio Cavalcanti Pereira.pdf: 280467 bytes, checksum: 8086a624ad0323f2488ae7dfba5c17d2 (MD5) / Made available in DSpace on 2016-07-05T18:07:15Z (GMT). No. of bitstreams: 1 Fabio Cavalcanti Pereira.pdf: 280467 bytes, checksum: 8086a624ad0323f2488ae7dfba5c17d2 (MD5) Previous issue date: 2006-02-22 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Bancroftian filariasis is a major public health problem in the tropics with 100 millions of people infected. It is a vector born infection and it is cause by Wuchereria bancrofti a parasite that lives in the human lymphatic vessels and lymph nodes affecting all ages and gender. The basic damage of the lymphatic system is lymphangiectasia which leads to lymphatic dysfunction producing lymphedema (elephantiasis), hydroecele and fistulization syndromes (chyluria, chylocele and lymph scrotum). The aim of this investigation was to study the relationship between the risk of developing fistulation syndrome and several parameters, such a amount of fat on the diet of patients assisted at Center for Teaching, Research and Tertiary Referral for bancroftian filariasis (NEPAF - Federal University of Pernambuco) in Recife, Brazil. The present study was carried out using the generalized linear models (GLMs) for the fitting of logistic model with the statistic program S-PLUS. / A Filariose Bancroftiana, ocorre como um dos maiores problemas de saúde púbica nos trópicos e afeta cerca de 100 milhões de indivíduos. Ë transmitida por um mosquito e causada pela Wuchereria bancrofti que vive nos vasos linfáticos e linfonodos dos seres humanos de todas as idades e ambos os sexos. O substrato anátomo-patológico da doença é a linfangiectasia que leva a uma disfunção linfática produzindo o linfedema (elefantíase), a hidrocele, e as síndromes de fistulização (quilúria, quilocele e linfoescroto). O objetivo dessa investigação se foi estudar a relação entre o risco de desenvolvimento das síndromes fistulizantes e vários parâmetros, tais como a quantidade de gordura na dieta de pacientes atendidos no Núcleo de Ensino, Pesquisa e Assistência em Filariose – NEPAF, Centro de Ciências da Saúde, UFPE. O presente estudo foi realizado usando-se a teoria dos modelos lineares generalizados (MLGs) para ajustar um modelo logístico para os dados da doença usando o programa estatístico S-PLUS.

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O objetivo deste trabalho é apresentar os conceitos relacionados a Teste Adaptativo Informatizado, ou abreviadamente TAI, para o modelo logístico unidimensional da Teoria de Resposta ao Item. Utilizamos a abordagem bayesiana para a estimação do parâmetro de interesse, chamado de traço latente ou habilidade. Apresentamos os principais algoritmos de seleção de itens em TAI e realizamos estudos de simulação para comparar o desempenho deles. Para comparação, usamos aproximações numéricas para o Erro Quadrático Médio e para o Vício e também calculamos o tempo médio para o TAI selecionar um item. Além disso, apresentamos como instalar e usar a implementação de TAI desenvolvida neste projeto chamada de TAI2U, que foi desenvolvido no VBA-Excel usando uma interface com o R / The main of this work is to introduce the subjects related to Computerized Adaptive Testing, or breafly CAT, for the unidimensional three-parameter logistic model of Item Response Theory. We use bayesian approach to estimate the parameter of interest. We present several item selection algorithms and we perform simulations comparing them. The comparisons are made in terms of the mean square error, bias of the trait estimates, the average time for item selection and the average length of test. Furthermore, we show how to install e use the CAT implementation of this work called built in MIcrosoft Excel - VBA using interface with the statistical package R

Objetivo: O objetivo desse estudo foi identificar a associação entre fatores clínicos e laboratoriais com o uso de insulina em gestantes com DMG no momento do diagnóstico e analisar os possíveis fatores preditores do uso de insulina. Método: Foram estudadas, de forma retrospectiva, 294 pacientes com diabetes melito gestacional (DMG) diagnosticado por meio do teste de tolerância à glicose oral de 100 gramas (TTGO-100g) entre 24 e 33 semanas completas de gestação, cujo seguimento pré-natal foi realizado ambulatorialmente pelo setor de Endocrinopatias e Gestação da Clínica Obstétrica do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, no período de 1 de julho de 2002 a 30 de junho de 2008. Os seguintes fatores clínicos e laboratoriais, que pudessem estar associados ao uso de insulina para controle glicêmico, foram analisados: idade materna, obesidade pré-gestacional - índice de massa corpórea (IMC) > 30 Kg/m2, antecedente familiar de diabetes melito (DM), tabagismo, hipertensão arterial, uso de corticosteróides sistêmicos, antecedente obstétrico de DMG e de macrossomia fetal, nuliparidade, multiparidade, antecedente obstétricos de natimortos e neomortos, idade gestacional no momento do diagnóstico, gemelidade, índice de líquido amniótico (ILA) aumentado ILA > 18 cm, polidrâmnio (ILA > 25 cm), número de valores anormais do TTGO-100g, glicemia de jejum anormal no TTGO- 100g glicemia de jejum > 95 mg/dL; média das quatro glicemias aferidas no TTGO-100g; valor da glicemia de jejum, de 1ª, 2ª e 3ª horas do TTGO-100g e hemoglobina glicada (HbA1c). A associação entre cada fator e a necessidade de insulinoterapia foi analisada individualmente (2 de Pearson / teste exato de Fisher e teste t de Student). O modelo de regressão logística para a análise multivariada foi usado para predizer a probabilidade desses fatores em relação ao uso de insulina. Resultados: Das 294 pacientes avaliadas, 39,8% (117/294) necessitaram de insulinoterapia para controle glicêmico. Observou-se correlação positiva entre o uso de insulina e obesidade pré-gestacional, antecedente familiar de DM, hipertensão arterial, antecedente obstétrico de DMG e de macrossomia fetal, número de valores anormais no TTGO-100g, glicemia de jejum > 95 mg/dL no TTGO-100g; média das quatro glicemias aferidas no TTGO-100g; valor da glicemia de jejum, de 1ª, 2ª e 3ª horas do TTGO-100g e HbA1c pela análise univariada (P<0,05). Na análise do modelo de regressão logística foram desenvolvidos dois modelos que incluíam os seguintes fatores preditores do uso de insulina: obesidade pré-gestacional, antecedente familiar de DM, número de valores anormais no TTGO-100g (só modelo 1) e valor da glicemia de jejum do TTGO-100g (só modelo 2). Os dois primeiros modelos foram novamente analisados, incluindo-se a variável HbA1c para verificação de sua contribuição na predição do uso de insulina. Curvas de probabilidade e escores foram construídos com base nas quatro combinações de fatores preditores. Conclusões: É possível estimar a probabilidade do uso de insulinoterapia para controle glicêmico em gestantes com DMG por meio de IMC pré-gestacional, antecedente familiar de DM, número de valores anormais do TTGO-100g, valor da glicemia de jejum no TTGO-100g e da HbA1c. / Objective: To determine the association between clinical and laboratory parameters and insulin requirement in pregnancies complicated by gestational diabetes mellitus (GDM), and to evaluate possible factors predicting the need for insulin therapy. Methods: A total of 294 patients with GDM diagnosed by the 100- g/3-h oral glucose tolerance test (OGTT) between 24 and 33 complete weeks of gestation were retrospectively studied. These patients were under prenatal follow-up at the Obstetric Clinic of the University of Sao Paulo School of Medicine (HCFMUSP) between July 1, 2002 and June 30, 2008. The clinical and laboratory factors which could be associated to the need for insulin therapy were analyzed: maternal age, prepregnancy obesity body mass index (BMI) > 30 Kg/m2, family history of diabetes mellitus (DM), smoking, hypertension, use of systemic corticosteroids, prior GDM, prior fetal macrosomia, nulliparity, multiparity, prior stillbirth, prior neonatal death, gestational age at diagnosis of GDM, multiple pregnancy, elevated amniotic fluid index (AFI) AFI > 18 cm, polyhydramnios (AFI > 25 cm), number of abnormal 100-g/3-h OGTT values, 100-g/3-h OGTT fasting plasma glucose > 95 mg/dL, mean of the four 100-g/3-h OGTT values, 100-g/3-h OGTT fasting/one/two/three plasma glucose values, and glycated hemoglobin (HbA1c). The association between each factor and the need for insulin therapy was then analyzed individually (Pearsons chi-square/Fishers exact or Student t test). The performance of these factors to predict the probability of insulin therapy was estimated using a logistic regression model. Results: Among the 294 patients studied, 39.8% (117/294) required insulin for glycemic control. Univariate analysis showed a positive correlation between insulin therapy and prepregnancy obesity, family history of diabetes, hypertension, prior GDM, prior fetal macrosomia, number of abnormal 100-g/3-h OGTT values, 100-g/3-h OGTT fasting plasma glucose > 95 mg/dL, mean of the four 100-g/3-h OGTT values, 100-g/3-h OGTT fasting/one/two/three plasma glucose values, and HbA1c (P < 0.05). Two logistic regression models were developed and included the following parameters: prepregnancy obesity, family history of diabetes, number of abnormal 100-g/3-h OGTT values (just model 1) and 100-g/3-h OGTT fasting plasma glucose (just model 2). The two first models were analysed another time including the variable HbA1c to verify its contribution on prediction of the need for insulin therapy. Probability curves and scores were constructed based on the four combinations of predictive factors. Conclusions: The probability of insulin therapy can be estimated in pregnant women with GDM based on prepregnancy obesity, family history of diabetes, number of abnormal 100-g/3-h OGTT values, 100-g/3-h OGTT fasting plasma glucose, and HbA1c concentration.

Alguns aspectos devem ser considerados nos trabalhos com frutíferas como o ponto adequado de colheita e estratégias de conservação, sendo fundamental a análise do crescimento e desenvolvimento dos frutos. Vários tipos de modelos estatísticos podem descrever os processos de crescimento envolvidos no sistema de produção vegetal, sendo os modelos não lineares considerados mais adequados para esse tipo de estudo. Para que os resultados obtidos no ajuste do modelo sejam válidos é necessário verificar a qualidade de ajuste por meio de uma análise dos resíduos. A distribuição dos resíduos ordinários para os modelos de regressão não linear, é matematicamente trabalhosa e os critérios de diagnóstico são falhos, principalmente em pequenas amostras. Diante de tal fato, Cook e Tsai (1985) definiram o resíduo projetado. O comportamento dos resíduos projetados é melhor do que o dos resíduos ordinários, pois suas propriedades são mais próximas das correspondentes ao resíduo ordinário da regressão normal linear. O ganho é substancial se o teste para a medida de não linearidade for significativo. Por meio dos ajustes dos modelos logístico e de Gompertz aos dados de comprimento de peras foi realizada a análise dos resíduos ordinários e dos resíduos projetados, a fim de evidenciar suas vantagens. Os resíduos projetados se mostraram viáveis para diagnóstico dos modelos e descartaram possíveis tendências apresentadas pelos resíduos normalizados. / Some aspects must be considered in the works with fruit tree such as the appropriate point of harvest and conservation strategies, being fundamental the analysis of growth and fruit developments. Several types of statistical models can describe the growth processes involved in plant production system and the non-linear models are considered more suitable for this type of study. For the results obtained from the model fit to be valid is necessary to check the quality of fit through a residual analysis. The distribution of the ordinary residuals in the non-linear regression models is mathematically complicated and the diagnostic criteria are not precise, mainly in small samples. To overcome this fact, Cook and Tsai (1985) defined the projected residual. The behaviour of the projected residuals is better than the ordinary residuals since their properties are closer to those corresponding to the ordinary residuals for the normal linear regression. The gain is substantial if the test for non-linearity is significant. Through the fit of the logistic and Gompertz models to the pears length data, it was performed an analysis of the ordinary and projected residuals in order to demonstrate their advantages. The projected residuals showed more feasible for the diagnostic of the models and ruled out possible trends presented by normalized residuals.

Objetivo: O objetivo desse estudo foi identificar a associação entre fatores clínicos e laboratoriais com o uso de insulina em gestantes com DMG no momento do diagnóstico e analisar os possíveis fatores preditores do uso de insulina. Método: Foram estudadas, de forma retrospectiva, 294 pacientes com diabetes melito gestacional (DMG) diagnosticado por meio do teste de tolerância à glicose oral de 100 gramas (TTGO-100g) entre 24 e 33 semanas completas de gestação, cujo seguimento pré-natal foi realizado ambulatorialmente pelo setor de Endocrinopatias e Gestação da Clínica Obstétrica do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, no período de 1 de julho de 2002 a 30 de junho de 2008. Os seguintes fatores clínicos e laboratoriais, que pudessem estar associados ao uso de insulina para controle glicêmico, foram analisados: idade materna, obesidade pré-gestacional - índice de massa corpórea (IMC) > 30 Kg/m2, antecedente familiar de diabetes melito (DM), tabagismo, hipertensão arterial, uso de corticosteróides sistêmicos, antecedente obstétrico de DMG e de macrossomia fetal, nuliparidade, multiparidade, antecedente obstétricos de natimortos e neomortos, idade gestacional no momento do diagnóstico, gemelidade, índice de líquido amniótico (ILA) aumentado ILA > 18 cm, polidrâmnio (ILA > 25 cm), número de valores anormais do TTGO-100g, glicemia de jejum anormal no TTGO- 100g glicemia de jejum > 95 mg/dL; média das quatro glicemias aferidas no TTGO-100g; valor da glicemia de jejum, de 1ª, 2ª e 3ª horas do TTGO-100g e hemoglobina glicada (HbA1c). A associação entre cada fator e a necessidade de insulinoterapia foi analisada individualmente (2 de Pearson / teste exato de Fisher e teste t de Student). O modelo de regressão logística para a análise multivariada foi usado para predizer a probabilidade desses fatores em relação ao uso de insulina. Resultados: Das 294 pacientes avaliadas, 39,8% (117/294) necessitaram de insulinoterapia para controle glicêmico. Observou-se correlação positiva entre o uso de insulina e obesidade pré-gestacional, antecedente familiar de DM, hipertensão arterial, antecedente obstétrico de DMG e de macrossomia fetal, número de valores anormais no TTGO-100g, glicemia de jejum > 95 mg/dL no TTGO-100g; média das quatro glicemias aferidas no TTGO-100g; valor da glicemia de jejum, de 1ª, 2ª e 3ª horas do TTGO-100g e HbA1c pela análise univariada (P<0,05). Na análise do modelo de regressão logística foram desenvolvidos dois modelos que incluíam os seguintes fatores preditores do uso de insulina: obesidade pré-gestacional, antecedente familiar de DM, número de valores anormais no TTGO-100g (só modelo 1) e valor da glicemia de jejum do TTGO-100g (só modelo 2). Os dois primeiros modelos foram novamente analisados, incluindo-se a variável HbA1c para verificação de sua contribuição na predição do uso de insulina. Curvas de probabilidade e escores foram construídos com base nas quatro combinações de fatores preditores. Conclusões: É possível estimar a probabilidade do uso de insulinoterapia para controle glicêmico em gestantes com DMG por meio de IMC pré-gestacional, antecedente familiar de DM, número de valores anormais do TTGO-100g, valor da glicemia de jejum no TTGO-100g e da HbA1c. / Objective: To determine the association between clinical and laboratory parameters and insulin requirement in pregnancies complicated by gestational diabetes mellitus (GDM), and to evaluate possible factors predicting the need for insulin therapy. Methods: A total of 294 patients with GDM diagnosed by the 100- g/3-h oral glucose tolerance test (OGTT) between 24 and 33 complete weeks of gestation were retrospectively studied. These patients were under prenatal follow-up at the Obstetric Clinic of the University of Sao Paulo School of Medicine (HCFMUSP) between July 1, 2002 and June 30, 2008. The clinical and laboratory factors which could be associated to the need for insulin therapy were analyzed: maternal age, prepregnancy obesity body mass index (BMI) > 30 Kg/m2, family history of diabetes mellitus (DM), smoking, hypertension, use of systemic corticosteroids, prior GDM, prior fetal macrosomia, nulliparity, multiparity, prior stillbirth, prior neonatal death, gestational age at diagnosis of GDM, multiple pregnancy, elevated amniotic fluid index (AFI) AFI > 18 cm, polyhydramnios (AFI > 25 cm), number of abnormal 100-g/3-h OGTT values, 100-g/3-h OGTT fasting plasma glucose > 95 mg/dL, mean of the four 100-g/3-h OGTT values, 100-g/3-h OGTT fasting/one/two/three plasma glucose values, and glycated hemoglobin (HbA1c). The association between each factor and the need for insulin therapy was then analyzed individually (Pearsons chi-square/Fishers exact or Student t test). The performance of these factors to predict the probability of insulin therapy was estimated using a logistic regression model. Results: Among the 294 patients studied, 39.8% (117/294) required insulin for glycemic control. Univariate analysis showed a positive correlation between insulin therapy and prepregnancy obesity, family history of diabetes, hypertension, prior GDM, prior fetal macrosomia, number of abnormal 100-g/3-h OGTT values, 100-g/3-h OGTT fasting plasma glucose > 95 mg/dL, mean of the four 100-g/3-h OGTT values, 100-g/3-h OGTT fasting/one/two/three plasma glucose values, and HbA1c (P < 0.05). Two logistic regression models were developed and included the following parameters: prepregnancy obesity, family history of diabetes, number of abnormal 100-g/3-h OGTT values (just model 1) and 100-g/3-h OGTT fasting plasma glucose (just model 2). The two first models were analysed another time including the variable HbA1c to verify its contribution on prediction of the need for insulin therapy. Probability curves and scores were constructed based on the four combinations of predictive factors. Conclusions: The probability of insulin therapy can be estimated in pregnant women with GDM based on prepregnancy obesity, family history of diabetes, number of abnormal 100-g/3-h OGTT values, 100-g/3-h OGTT fasting plasma glucose, and HbA1c concentration.

L'esca de la vigne fait partie des maladies de dépérissement incurables dont l'étiologie n'est pas complément élucidée. Elle représente un des problèmes majeurs en viticulture. L'objectif général de cette thèse est d'améliorer la compréhension des processus épidémiques et des facteurs de risque. Pour ce faire, nous avons mené une étude quantitative du développement spatio-temporel de l'esca à l'échelle de la parcelle. Dans un premier temps, pour détecter d'éventuelles corrélations spatiales entre les cas de maladie, des tests statistiques non paramétriques sont appliqués aux données spatio-temporelles d'expression foliaires de l'esca pour 15 parcelles du bordelais. Une diversité de profils spatiaux, allant d'une distribution aléatoire à fortement structurée est trouvée. Dans le cas de structures très agrégées, les tests n'ont pas montré d'augmentation significative de la taille des foyers, ni de propagation secondaire locale à partir de ceps symptomatiques, suggérant un effet de l'environnement dans l'explication de cette agrégation. Dans le but de modéliser l'occurrence des symptômes foliaires, nous avons développé des modèles logistiques hiérarchiques intégrant à la fois des covariables exogènes liées à l'environnement et des covariables de voisinage de ceps déjà malades mais aussi un processus latent pour l'auto-corrélation spatio-temporelle. Les inférences bayésiennes sont réalisées en utilisant la méthode INLA (Inverse Nested Laplace Approximation). Les résultats permettent de conforter l'hypothèse du rôle significatif des facteurs environnementaux dans l'augmentation du risque d'occurrence des symptômes. L'effet de propagation de l'esca à petite échelle à partir de ceps déjà atteints situés sur le rang ou hors rang n'est pas montré. Un modèle autologistique de régression, deux fois centré, qui prend en compte de façon plus explicite la structure spatio-temporelle de voisinage, est également développé. Enfin, une méthode géostatistique d'interpolation de données de nature anisotropique atypique est proposée. Elle permet d'interpoler la variable auxiliaire de résistivité électrique du sol pour estimer à l'échelle de chaque plante de la parcelle, la réserve en eau du sol disponible pour la vigne. Les méthodes géostatistique et spatio-temporelles développées dans cette thèse ouvrent des perspectives pour identifier les facteurs de risques et prédire le développement de l'esca de la vigne dans des contextes agronomiques variés. / Esca grapevine disease is one of the incurable dieback disease with the etiology not completely elucidated. It represents one of the major threats for viticulture around the world. To better understand the underlying process of esca spread and the risk factors of this disease, we carried out quantitative analyses of the spatio-temporal development of esca at vineyard scale. In order to detect the spatial correlation among the diseased vines, the non-parametric statistical tests were applied to the spatio-temporal data of esca foliar symptom expression for 15 vineyards in Bordeaux region. Among vineyards, a large range of spatial patterns, from random to strongly structured, were found. In the vineyards with strongly aggregated patterns, no significant increase in the size of cluster and local spread from symptomatic vines was shown, suggesting an effect of the environment in the explanation of this aggregation. To model the foliar symptom occurrence, we developed hierarchical logistic regression models by integrating exogenous covariates, covariates of neighboring symptomatic vines already diseased, and also a latent process with spatio-temporal auto-correlation. The Bayesian inferences of these models were performed by INLA (Inverse Nested Laplace Approximation) approach. The results confirmed the effect of environmental factors on the occurrence risk of esca symptom. The secondary locally spread of esca from symptomatic vines located on the same row or out of row was not shown. A two-step centered auto-logistic regression model, which explicitly integrated the spatio-temporal neighboring structure, was also developed. At last, a geostatistical method was proposed to interpolate data with a particular anisotropic structure. It allowed interpolating the ancillary variable, electrical resistivity of soil, which were used to estimate the available soil water content at vine-scale. These geostatistical methods and spatio-temporal statistical methods developed in this thesis offered outlook to identify risk factors, and thereafter to predict the development of esca grapevine disease in different agronomical contexts.

從1960年代開始，公部門基於稅務處理需求，使得電腦輔助大量估價（Computer Assisted Mass Assessment，CAMA）成為輔助的工具，大幅提升了估價的效率。在1990年代，金融機構因不動產證券化的發展及不良資產估價等業務，而衍生了對大量不動產進行估價的需求，同時在電腦與統計模型的進步之下，自動估價模型（Automated Valuation Models，AVM）應然而生，並被廣泛應用在金融市場。由此可知因為不動產經濟活動的熱絡發展，大量估價的需求日益增加，其具備的客觀與效率等優點更彰顯其重要性。 雖然大量估價的需求日益增加，然而過去對於估價準確性相關研究，主要著重在估價理論與技術層面、估價行為對估價結果的影響、探討個別估價和大量估價的估值比較，而較少單獨探究影響大量估價準確性的因素。由於特徵價格理論隱含不動產高度異質的特性，不動產價格受到總體經濟、政策、住宅屬性、公共設施、區位等因素影響，然而前述因素是否會對估價準確性造成影響?造成影響的因素為何?為本文所欲探討之問題。 本文在實證部分分成兩階段，首先以特徵價格理論為基礎，利用實價登錄資料建立大量估價模型，以MAPE與Hit Rate來衡量估價準確性，結果指出MAPE達到14.19%，而正負誤差10%的命中率為47.18%、正負誤差20%的命中率為74.75%，跟過往研究所建立的大量估價模型相比具有相當的水準，顯示出官方性質的交易資料具有一定的可信度。在建置大量估價模型後，本文以模型價格及成交價格間的比值作為劃分估價準確程度的依據，以多項羅吉特模型進行實證分析，結果指出住宅大樓、捷運站周遭住宅、大坪數住宅估價結果容易呈現低估情形；而新市區中心估價結果容易呈現高估的情形；另外比較特別的是舊市區中心、北郊區估價結果較容易呈現高估及低估，換言之在這兩個區域估價容易得到不準確的結果。 / Since 1960s, public sector began to take advantage of computer assisted mass assessment(CAMA) based on taxation services and greatly improved the efficiency of appraisal. In 1990s, financial institutions due to the development of securitization of real estate and non-performing asset valuation and other services, generating the demand of mass appraisal. Simultaneously, due to the development of computer and statistical models gradually progress, bring in automated valuation models(AVM) in the financial markets. Hence, with the real estate economic activities gradually booming, the increasing demand for mass appraisal, which has the objective of efficiency and other advantages will be more to highlight its importance. While the increasing demand for mass appraisal, but past studies about the accuracy of appraisal, mainly focused on the theoretical and technical aspects, the impact of behavior on the valuation results, and to explore appraisers and mass appraisal of the valuation. However, past studies less focused on a large number of factors affect the accuracy of the appraisal. Since the hedonic price theory implies highly heterogeneous characteristics of real estate, real estate prices affected by factors of macroeconomic, tax policy, housing properties, public facilities, location and so on, but whether the aforementioned factors will affect the valuation accuracy?Is this research seeking to explore the issue. In this paper, the empirical section is divided into two stages, first with the hedonic price theory based on the use actual price registration to establish the mass appraisal models, and base on MAPE and Hit Rate to measure the accuracy of the appraisal, the results indicate MAPE reached 14.19%, while the margin of error of 10% hit rate of 47.18%, 20% hit rate is 74.75%. Compared with the past studies, this model has established a great performance. This research proved that the official data with reliability. After establishing the mass appraisal models, the research use model prices and the transaction price ratio as the basis for division between the accuracy of the appraisal and use multinomial logistic model to conduct empirical analysis. The results indicated that the residential building, housing around MRT stations, the big area housing was prone to result underestimate valuations, the new urban center appraisal results likely to show overvalued valuations. On the other hand, old city center and the northern suburbs results presented overestimate and underestimate valuations simultaneously, in other words, that is usually get inaccurate results in these two regions.

There is significant interest by the food industry in applying milder processing conditions. A major area of research within predictive modelling has been the search for models which accurately predict the effect of combining multiple processes or hurdles. For a mild process, which has temperature as the major microbial injury step, the effect of the other combined hurdles in inhibiting growth of the injured organisms must be understood. The latter means that the inoculum size dependency of the time to growth must also be fully understood. This essentially links injury steps with the potential for growth. Herein, we have been developing the use of optical density (O.D) for obtaining growth rates and lag times using multiple inocula rather than using the traditional methods which use one single inoculum. All analyses were performed in the Bioscreen analyser which measures O.D. The time to detection (TTD) was defined as the time needed for each inoculum to reach an O.D=0.2 and O.D was related to microbial numbers with simple calibration curves. Several primary models were used to predict growth curves from O.D data and it was shown that the classic logistic, the Baranyi and the 3-phase linear model (3-PLM) were the most capable primary models of those examined while the modified Gompertz and modified logistic could not reproduce TTD data. Using the Malthusian approximation of the logistic model the effect of mild temperature shifts was studied. The data obtained showed that for mild temperature shifts, growth rates quickly changed to the new environment without the induction of lags. The growth of Listeria monocytogenes, Salmonella Typhimurium and Escherichia coli was studied at 30⁰C and/or 37⁰C, in different NaCl concentrations, pH and their combinations. The classical 3-parameter logistic with lag model was rearranged to provide the theoretical foundation for the observed TTD and accurate growth rates and lag times could be estimated. As the conditions became more unfavourable, the lag time increased while the growth rate decreased. Also, the growth rate was found to be independent from the inoculum size; the inoculum size affected only the TTD. The Minimum Inhibitory Concentration (MICNaCl and MICpH) was calculated using the Lambert and Pearson model (LPM) and also the Growth/No Growth (G/NG) interface was determined using combinations of NaCl and pH. These data were transformed in rate to detection (RTD) and fitted with a response surface model (RSM) which was subsequently compared with the Extended LPM (ELPM). The LPM and the ELPM could analyse results from individual and combined inhibitors, respectively. Following a mild thermal process a lag due to thermal injury was also induced, the magnitude of which was dependent on the organism and environmental conditions; the observed distribution of the lags appeared, in general, to follow the Log-normal distribution. After the lag period due to injury, growth recommenced at the rate dictated by the growth environment present. Traditional growth curves were constructed and compared with the data obtained from the Bioscreen under the same conditions. From the results obtained, it can be suggested that the increased lag times and growth rates obtained from the traditional plate counts compared with the values obtained from the Bioscreen microbiological analyser, might be an artifact of the plating method or may be due to the use of the modified Gompertz to study the growth. In conclusion, O.D can be used to accurately determine growth parameters, to give a better understanding and quantify the G/NG interface and to examine a wealth of phenomena such as fluctuating temperatures and mild thermal treatments. The comparison between the traditional growth curves against the data obtained from the Bioscreen showed that the TTD method is a rapid, more accurate and cheaper method than the traditional plate count method which in combination with the models developed herein can offer new possibilities both to the research and the food industry.